Spring drought forecasting in mainland Portugal based on large-scale climatic indices
The success of a strategy of mitigation of the effects of the droughts requires the implementation of an effective monitoring and forecasting system, able to identify drought events and follow their spatiotemporal evolution. This article demonstrates the capability of the artificial neural networks...
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Language: | Spanish |
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Universitat Politècnica de València
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ftunpvalenciaojs:oai:polipapers.upv.es:article/4109 2023-09-05T13:21:46+02:00 Spring drought forecasting in mainland Portugal based on large-scale climatic indices Previsão de secas na primavera em Portugal Continental com base em indicadores climáticos de larga escala Santos, J.F Portela, M.M. Pulido-Calvo, I. 2015-10-30 application/pdf http://polipapers.upv.es/index.php/IA/article/view/4109 https://doi.org/10.4995/ia.2015.4109 spa spa Universitat Politècnica de València http://polipapers.upv.es/index.php/IA/article/view/4109/4368 http://polipapers.upv.es/index.php/IA/article/view/4109 doi:10.4995/ia.2015.4109 Derechos de autor 2015 Ingeniería del agua Ingeniería del Agua; Vol. 19 No. 4 (2015); 211-227 Ingeniería del Agua; Vol. 19 Núm. 4 (2015); 211-227 1886-4996 1134-2196 Artificial neural networks Hindcasting SPI NAO SST Redes neuronais artificiais info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article 2015 ftunpvalenciaojs https://doi.org/10.4995/ia.2015.4109 2023-08-16T06:28:07Z The success of a strategy of mitigation of the effects of the droughts requires the implementation of an effective monitoring and forecasting system, able to identify drought events and follow their spatiotemporal evolution. This article demonstrates the capability of the artificial neural networks in predicting the spring standardized precipitation index, SPI, for Portugal. The validation of the models used the hindcasting, which is a technique by which a given model is tested through its application to historical data followed by the comparison of the results thus achieved with the data. The SPI index was calculated at the timescale of six months and the climate indices used as external predictors in the hindcasting were the North Atlantic Oscillation and temperatures of the sea surface. The study showed the added value of the inclusion of previous predictors in the model. Maps of the probabilities of the drought occurrences which may be very important for integrated planning and management of water resources were also developed. O sucesso de uma estratégia de mitigação dos efeitos da seca passa pela implementação de um sistema de monitorização e previsão eficaz, capaz de identificar os eventos de seca e de seguir a sua evolução espácio-temporal. Neste artigo demonstrase a eficiência de redes neuronais artificiais na previsão, para Portugal, do índice de precipitação padronizada, SPI, relativo à primavera. A validação dos modelos recorreu ao hindcasting, designando-se, por tal, a técnica através da qual um dado modelo é testado mediante a sua aplicação a períodos temporais históricos, com comparação dos resultados obtidos com as respectivas observações. O índice SPI foi calculado à escala temporal de 6 meses tendo o hindcast utilizado como indicadores climáticos a oscilação do Atlântico Norte e temperaturas da superfície do mar. O estudo evidenciou a mais valia da inclusão dos anteriores predictores externos no modelo de previsão. Elaboraram-se, ainda, mapas de probabilidade de ocorrência de seca os quais ... Article in Journal/Newspaper North Atlantic North Atlantic oscillation Universitat Politècnica de València: PoliPapers Larga ENVELOPE(-60.767,-60.767,-62.467,-62.467) Ingeniería del agua 19 4 211 |
institution |
Open Polar |
collection |
Universitat Politècnica de València: PoliPapers |
op_collection_id |
ftunpvalenciaojs |
language |
Spanish |
topic |
Artificial neural networks Hindcasting SPI NAO SST Redes neuronais artificiais |
spellingShingle |
Artificial neural networks Hindcasting SPI NAO SST Redes neuronais artificiais Santos, J.F Portela, M.M. Pulido-Calvo, I. Spring drought forecasting in mainland Portugal based on large-scale climatic indices |
topic_facet |
Artificial neural networks Hindcasting SPI NAO SST Redes neuronais artificiais |
description |
The success of a strategy of mitigation of the effects of the droughts requires the implementation of an effective monitoring and forecasting system, able to identify drought events and follow their spatiotemporal evolution. This article demonstrates the capability of the artificial neural networks in predicting the spring standardized precipitation index, SPI, for Portugal. The validation of the models used the hindcasting, which is a technique by which a given model is tested through its application to historical data followed by the comparison of the results thus achieved with the data. The SPI index was calculated at the timescale of six months and the climate indices used as external predictors in the hindcasting were the North Atlantic Oscillation and temperatures of the sea surface. The study showed the added value of the inclusion of previous predictors in the model. Maps of the probabilities of the drought occurrences which may be very important for integrated planning and management of water resources were also developed. O sucesso de uma estratégia de mitigação dos efeitos da seca passa pela implementação de um sistema de monitorização e previsão eficaz, capaz de identificar os eventos de seca e de seguir a sua evolução espácio-temporal. Neste artigo demonstrase a eficiência de redes neuronais artificiais na previsão, para Portugal, do índice de precipitação padronizada, SPI, relativo à primavera. A validação dos modelos recorreu ao hindcasting, designando-se, por tal, a técnica através da qual um dado modelo é testado mediante a sua aplicação a períodos temporais históricos, com comparação dos resultados obtidos com as respectivas observações. O índice SPI foi calculado à escala temporal de 6 meses tendo o hindcast utilizado como indicadores climáticos a oscilação do Atlântico Norte e temperaturas da superfície do mar. O estudo evidenciou a mais valia da inclusão dos anteriores predictores externos no modelo de previsão. Elaboraram-se, ainda, mapas de probabilidade de ocorrência de seca os quais ... |
format |
Article in Journal/Newspaper |
author |
Santos, J.F Portela, M.M. Pulido-Calvo, I. |
author_facet |
Santos, J.F Portela, M.M. Pulido-Calvo, I. |
author_sort |
Santos, J.F |
title |
Spring drought forecasting in mainland Portugal based on large-scale climatic indices |
title_short |
Spring drought forecasting in mainland Portugal based on large-scale climatic indices |
title_full |
Spring drought forecasting in mainland Portugal based on large-scale climatic indices |
title_fullStr |
Spring drought forecasting in mainland Portugal based on large-scale climatic indices |
title_full_unstemmed |
Spring drought forecasting in mainland Portugal based on large-scale climatic indices |
title_sort |
spring drought forecasting in mainland portugal based on large-scale climatic indices |
publisher |
Universitat Politècnica de València |
publishDate |
2015 |
url |
http://polipapers.upv.es/index.php/IA/article/view/4109 https://doi.org/10.4995/ia.2015.4109 |
long_lat |
ENVELOPE(-60.767,-60.767,-62.467,-62.467) |
geographic |
Larga |
geographic_facet |
Larga |
genre |
North Atlantic North Atlantic oscillation |
genre_facet |
North Atlantic North Atlantic oscillation |
op_source |
Ingeniería del Agua; Vol. 19 No. 4 (2015); 211-227 Ingeniería del Agua; Vol. 19 Núm. 4 (2015); 211-227 1886-4996 1134-2196 |
op_relation |
http://polipapers.upv.es/index.php/IA/article/view/4109/4368 http://polipapers.upv.es/index.php/IA/article/view/4109 doi:10.4995/ia.2015.4109 |
op_rights |
Derechos de autor 2015 Ingeniería del agua |
op_doi |
https://doi.org/10.4995/ia.2015.4109 |
container_title |
Ingeniería del agua |
container_volume |
19 |
container_issue |
4 |
container_start_page |
211 |
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1776202348456050688 |